Success of any needle-based medical procedures depends on accurate placement of the needle at the target location. However, accurate targeting and control of flexible self-actuating (active) needle are challenging. We have developed a shape memory alloy-actuated flexible needle steered by a 3D Cartesian robot and performed a comparative study of four, non-model-based, coordinated control methodologies for the combined robot steering and flexible-needle insertion process for surgical interventions. Investigated four controllers are: proportional–integral–derivative (PID), PID with the cubic of positional error term (PID-P3), static PID sliding mode controller, and robust adaptive PID sliding mode controller (RAPID-SMC). Relative efficacies of these controllers are demonstrated by performing experiements using a tissue-mimicking soft material phantom. Results from experiments have reavealed that RAPID-SMC is superior to other three controllers.

In this paper, the k-valued logic control network is introduced to study the cooperative pursuit control problem of multiple underactuated underwater vehicles (UUVs) with time delay in three-dimensional space. The semi-tensor product of matrices is used to solve the complex calculation problem of the large dimension matrix. The influence of communication delay on multiple UUVs’ optimization and cooperative pursuit control is expressed in a matrix. Under the leadership of evader UUV, the control algorithm can ensure that all the pursuit UUVs reach the desired position. The stability of the closed loop system is proved.

The gas temperature of the supersonic heat airflow simulated test system is mainly determined by the fuel and air flow rates which enter the system combustor. In order to realise a high-quality control of gas temperature, in addition to maintaining the optimum ratio of fuel and air flow rates, the dynamic characteristics of them in the combustion process are also required to be synchronised. Aiming at the coordinated control problem of fuel and air flow rates, the mathematical models of fuel and air supply subsystems are established, and the characteristics of the systems are analysed. According to the characteristics of the systems and the requirements of coordinated control, a fuzzy-PI cross-coupling coordinated control strategy based on neural sliding mode predictive control is proposed. On this basis, the proposed control algorithm is simulated and experimentally studied. The results show that the proposed control algorithm has good control performance. It cannot only realise the accurate control of fuel flow rate and air flow rate, but also realise the coordinated control of the two.

This paper presents a novel scheme for achieving attitude control of a tumbling combination system in the post-capture phase of a tethered space robot (TSR). Given the combination rotation characteristics, tether force is applied to provide greater control torques for stabilising the attitude. The proposed control scheme involves two attitude controllers, which coordinate the controller of the tether force and thruster force and the controller of single thruster force. The numerical simulations include a comparison between this coordinated control and the traditional thruster control and a sensitivity analysis on initial values of parameters. Simulation results validate the feasibility of the attitude control scheme for a tumbling combination system, and fuel consumption of the attitude control is efficiently reduced using the coordinated control strategies.